About the job

We're ASOS, the online retailer for fashion lovers all around the world.

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgement, and channel your creativity into a platform used by millions.

Everyone needs some help showing up as their best self. We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process

Job Description

We’re looking for a Senior BI Engineer to work along with our BI team in FinTech and Fashion Tech. Reporting to the Staff Engineering Lead, you will take the strategy they set and turn it into delivery, leading the team day to day and being the senior, most experienced pair of hands on the data side.

The team owns reporting and BI across all of FinTech and Fashion Tech. That covers the reports our business runs on, the reconciliations that keep our data feeds honest, and ownership of the data warehouse and the data sync between our ERP and the wider estate.

Our stack is Python, PySpark, Delta Lake and Databricks, with T‑SQL, Kimball dimensional modelling and Power BI on top, working closely with Microsoft Dynamics 365 Finance and Operations data structures. We are currently reviewing whether to move from Databricks to Microsoft Fabric, so you should be comfortable working through a platform decision and the migration that may follow.

Key Responsibilities

Being Mentor to the BI Team

• Support the BI team day to day, turning the strategy set by the Staff Engineering Lead into a plan the team can deliver against.
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• Support and mentor the other BI Engineers on both reports and the data side, through design reviews, pairing and code review.
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• Be the senior technical voice in the team. Set the standards for how we model, build and test, and raise the bar on quality.
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• Prioritise and balance the team’s work across reporting requests, reconciliations and platform work, and pick up the hardest builds yourself.
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Owning the Data Warehouse and Data Sync

• Own our data warehouse, including the dimensional model, the pipelines that load it and the standards that keep it consistent as it grows.
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• Own the data sync between our ERP and the warehouse, making sure data lands completely, on time and in a shape the business can use.
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• Build and maintain the reconciliations that prove our feeds are complete and accurate, and investigate and fix them when they break.
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Reporting and BI Delivery

• Deliver reporting our stakeholders trust, from the models underneath through to well built, performant Power BI reports.
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• Design and build data pipelines in Python, PySpark and Delta Lake, and write the T‑SQL behind our models and reconciliations.
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• Keep an eye on cost, performance and reliability across the platform, and keep improving what is already live.
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Working with Stakeholders

• Work with stakeholders across Finance, Tech and Fashion, including our Commercial, Buying and Product colleagues, to understand what they need from their data.
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• Turn reporting requests into well shaped requirements, and challenge constructively when an existing report or a different cut of the data would do the job.
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• Keep stakeholders updated on progress, priorities and any risks to the data they depend on, so there are no surprises.
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Working Across Tech

• Work closely with the solution, engineering and support teams across FinTech and Fashion Tech, so changes upstream in the ERP don’t break reporting downstream.
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• Follow the wider ASOS delivery process, including governance, change control and release cadence, and run the team’s work through Azure DevOps.
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• Work with Architecture, Security and Risk so what we build meets ASOS standards, protects sensitive financial data and stands up to audit.
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Why This Role Matters

Almost every decision our Finance and commercial teams make rests on numbers this team produces, from month end close and supplier payments through to trading, stock and range performance. If the warehouse is wrong or a feed silently drops data, people make the wrong call.

This role is where that quality is set. We need someone senior enough to own the warehouse and the ERP data sync end to end, lead a team through a possible platform move, and still be close enough to the detail to build the hard things themselves.

Qualifications

Data and BI Experience

• Strong hands-on experience with Python, SQL, PySpark and Delta Lake for building scalable data pipelines.
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• Experience across the Azure data stack, including Azure Data Factory (ADF), Azure Functions, Logic Apps and Azure Storage.
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• Strong experience with Databricks and Microsoft Fabric, including Lakehouse and modern data engineering solutions.
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• Strong SQL/T-SQL skills and experience with Kimball dimensional modelling and data warehouse design.
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• Experience integrating ERP data, ideally Microsoft Dynamics 365 Finance & Operations or other major ERP platforms.
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• Working knowledge of Power BI, DAX and data modelling, with a focus on delivering effective business reporting.
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Leadership

• Experience leading or mentoring other engineers, setting technical standards and lifting the quality of what a team produces.
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• Comfortable taking a strategy someone else has set and turning it into a plan your team can deliver.
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• Able to prioritise across competing requests and make a clear call on what gets done and what waits.
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Stakeholder Management and Rigour

• Confident with stakeholders across Finance, Tech and the commercial teams, able to explain data simply and push back when a request doesn’t stack up.
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• A genuine eye for data quality, with the patience to chase a reconciliation break until you find the root cause.
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• Organised and calm under pressure, particularly around month end and peak trading.
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We’d Also Love to See

• Experience of a lakehouse or warehouse migration, or of working through a platform decision such as Databricks to Microsoft Fabric.
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• Knowledge of finance or supply chain processes such as procure to pay, order to cash, month end close or stock and warehouse operations.
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• Experience in retail, ecommerce or fashion, particularly reporting for buying, merchandising or trading.
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• Experience with CI/CD for data, testing frameworks, data observability or governance and cataloguing tools.
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Why You’ll Love This Role

• You will own the data warehouse and the ERP data sync for two of the most important areas of ASOS.
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• It is a rare mix. You get to lead and mentor a team, set the technical standards, and still build the hard things yourself.
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• A modern stack with a genuine platform decision ahead, and a real say in where we take it.
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• Broad exposure across Finance, Commercial, Buying and Product, with work that visibly shapes how ASOS makes decisions.
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Additional Information

BeneFITS’

• Employee discount (hello ASOS discount!)
• Employee sample sales
• 25 days paid annual leave + an extra celebration day for a special moment
• Discretionary bonus scheme
• Private medical care scheme
• Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
• Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role

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About the job

Senior Data / Platform Engineer (Azure)

Guildford, UK (Remote with occasional office visit)

Permanent (or) Contract (Inside IR35)

Tech Stack: Azure Databricks + PySpark/Python + Azure Synapse + ADLS Gen2 + Azure Platform + Terraform/Pulumi + CI/CD

Job Description:

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Overall Objectives of the Job

We are seeking a skilled and experienced Senior Data / Platform Engineer to join our Data & Analytics team. This hybrid role combines hands-on data engineering on Databricks and Azure Synapse with platform administration responsibilities across our cloud data estate. The role holder will design, build, and operate scalable data pipelines while also maintaining the underlying Azure platform — including infrastructure-as-code (Pulumi), CI/CD automation, monitoring, security, and Databricks workspace administration. The ideal candidate combines strong Python/PySpark engineering skills with deep Azure platform knowledge and a service-excellence mindset, ensuring the client's Data Technology platform remains secure, reliable, and aligned to Client's standards.

Duties and Responsibilities:

Lead solution design activities, collaborating with peers and mentoring junior colleagues to define and execute the team backlog.

Develop, test, and document scalable ETL/ELT data pipelines and workflows using Databricks and Azure Synapse to ingest and transform data from a variety of sources.

Administer and maintain Azure data platform components including Synapse, Databricks, ADLS Gen2, Key Vault, networking (VNets, NSGs, Managed Private Endpoints) and access control (RBAC, ACLs).

Manage infrastructure-as-code across Dev, Staging, and Production environments using Pulumi (and equivalents such as Terraform / Bicep).

Design and operate CI/CD pipelines using GitHub Actions (with OIDC federation) and/or Azure DevOps, supporting trunk-based development practices.

Administer Databricks workspaces — cluster policies, Secret Scopes, Repos/Git integration, Workflow job health, and Unity Catalog governance.

Monitor platform and pipeline health using Azure Monitor, Log Analytics, KQL, and Azure Dashboards; triage and resolve incidents.

Implement robust data security and ensure compliance with data privacy regulations; manage service principals, Managed Identities, and least-privilege access.

Carry out routine platform operations: patching, backups, storage lifecycle, tagging, access reviews, DR readiness, and runbook execution.

Identify and address performance bottlenecks and data quality issues to ensure data accuracy and reliability.

Work with testers to ensure automated test plans are in place and agree test packs for UAT; review peers' work and take accountability for the quality of squad deliverables.

Collaborate with stakeholders and analysts to understand data requirements and deliver clean, reliable, accessible data.

Ensure solution designs align with the client's Data Technology Strategy, maintaining and enhancing client's standards and Service Excellence.

Maintain technical documentation to Client's standards (e.g., Grimlock) and stay current with industry trends, driving continuous improvement and innovation.

Qualification, Experience, Technical and Functional Skills

Bachelor's or Master's degree in Computer Science, Information Systems, or a related field, with relevant experience in data engineering and Azure platform administration.

Must Have

Databricks: hands-on experience building and optimizing pipelines, managing Delta Lake, and administering workspaces (cluster policies, Unity Catalog, Secret Scopes, Workflows).

Python / PySpark: strong programming skills for data processing, automation, and scripting.

Azure data stack: Synapse, Databricks, ADLS Gen2, Key Vault — including Linked Services, Managed Identity, and Spark Pool configuration.

Azure platform fundamentals: compute, storage, networking (VNets, NSGs, Private Endpoints), identity and RBAC.

CI/CD: GitHub Actions (with OIDC federation) and/or Azure DevOps for data and platform deployments.

Infrastructure-as-Code: Pulumi (or Terraform / Bicep) across multiple environments.

Scripting: PowerShell and Bash for platform automation.

Monitoring & observability: Azure Monitor, Log Analytics, KQL.

Big data file formats: Parquet and Delta Lake.

Cloud-native data modelling and ETL/ELT frameworks on Azure.

Good to Have

Azure certifications: AZ-104, AZ-400, DP-203.

Azure Data Factory (ADF), Microsoft Purview, Microsoft Fabric.

Data governance: lineage, cataloguing, sensitivity labels.

Event-driven architectures: Kafka / Azure Event Hubs.

Delta Live Tables, MLflow.

IDMC Secure Agent, Power Automate flows.

Security baselines: CIS / NIST.

Observability tooling: OpenTelemetry, Datadog.

AI tools and their application in data engineering.

Knowledge of the UK Insurance Market.

Agile / Scrum delivery experience.